Deterministic Fair-Share Tip Splitter MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 1 tools to Split Bill

Name: Deterministic Fair-Share Tip Splitter
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Deterministic Fair-Share Tip Splitter through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Ask AI about this MCP Server for OpenAI Agents SDK

Open in ChatGPT Open in Claude Open in Perplexity

The Deterministic Fair-Share Tip Splitter MCP Server for OpenAI Agents SDK is a standout in the Productivity category — giving your AI agent 1 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Deterministic Fair-Share Tip Splitter Assistant",
            instructions=(
                "You help users interact with Deterministic Fair-Share Tip Splitter. "
                "You have access to 1 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Deterministic Fair-Share Tip Splitter"
        )
        print(result.final_output)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Deterministic Fair-Share Tip Splitter MCP Server

Splitting a restaurant bill with shared appetizers, individual drinks, and group tips is a mathematical nightmare for LLMs. They frequently hallucinate decimal distributions and fail to balance the final grand total. The Tip Splitter MCP offloads this exact calculation to a rigorous V8 mathematical engine.

The OpenAI Agents SDK auto-discovers all 1 tools from Deterministic Fair-Share Tip Splitter through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Deterministic Fair-Share Tip Splitter, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

The Superpowers

Proportional Taxation & Tipping: The engine automatically calculates each person's base subtotal based on the specific items they consumed (or shared), and then proportionally applies the exact tax and tip burden to each individual.
Penny Reconciliation Algorithm: When fractional cents create a discrepancy between the calculated individual totals and the actual receipt grand total, the engine automatically reconciles the missing or extra penny to guarantee 100% mathematical closure.
Shared Consumption Mapping: Allows mapping a single item (like 'Nachos') to multiple consumers (e.g., 'Alice' and 'Bob'). The engine dynamically splits the price before applying secondary rates.
Zero-Dependency Execution: Operates entirely natively within the V8 runtime, guaranteeing extreme speed and precision without pulling heavy external libraries.

The Deterministic Fair-Share Tip Splitter MCP Server exposes 1 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 1 Deterministic Fair-Share Tip Splitter tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to Deterministic Fair-Share Tip Splitter through Vinkius, your AI agent gets direct access to every tool listed below — spanning math-precision, billing, tax-calculation, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

split

Split bill on Deterministic Fair-Share Tip Splitter

You must provide the items as a stringified JSON array, along with the total taxAmount and tipPercentage. Deterministically calculates individual bill shares, proportionally distributing taxes and tips among consumers based on their exact items, and resolving rounding discrepancies

Connect Deterministic Fair-Share Tip Splitter to OpenAI Agents SDK via MCP

Follow these steps to wire Deterministic Fair-Share Tip Splitter into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 1 tools from Deterministic Fair-Share Tip Splitter

Why Use OpenAI Agents SDK with the Deterministic Fair-Share Tip Splitter MCP Server

OpenAI Agents SDK provides unique advantages when paired with Deterministic Fair-Share Tip Splitter through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Deterministic Fair-Share Tip Splitter + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Deterministic Fair-Share Tip Splitter MCP Server delivers measurable value.

Automated workflows: build agents that query Deterministic Fair-Share Tip Splitter, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Deterministic Fair-Share Tip Splitter, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Deterministic Fair-Share Tip Splitter tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Deterministic Fair-Share Tip Splitter to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Deterministic Fair-Share Tip Splitter in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Deterministic Fair-Share Tip Splitter immediately.

"Split this bill: Burger ($15) for Alice, Salad ($12) for Bob, and shared Nachos ($10) for both. Tax is $3.50 and tip is 20%."

"Three of us had a $90 steak dinner (all shared). Tax $8, tip 15%. How much each?"

"Calculate the fair split for a $45 bill where John had a $30 wine and Sarah had a $15 pasta. Tax $4, tip 18%."

Troubleshooting Deterministic Fair-Share Tip Splitter MCP Server with OpenAI Agents SDK

Common issues when connecting Deterministic Fair-Share Tip Splitter to OpenAI Agents SDK through Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Deterministic Fair-Share Tip Splitter + OpenAI Agents SDK FAQ

Common questions about integrating Deterministic Fair-Share Tip Splitter MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.

Explore More MCP Servers

View all →

Pagar.me

11 tools

Create orders, manage subscriptions, and process Pix/Boleto payments via Pagar.me API.

Zendesk Sell

11 tools

Manage sales leads, contacts, and deals via the Zendesk Sell (Base CRM) API.

SendGrid Email Sender

1 tools

This MCP does exactly one thing: it sends transactional emails using Twilio SendGrid. That's its only function, and nothing else. Incredible for giving your AI agents the ability to dispatch email reports.

Couchbase (Vector & NoSQL)

7 tools

Manage vector search and NoSQL via Couchbase — execute N1QL queries, perform KNN vector searches, and audit documents directly from any AI agent.